Application of Screening Methods, Shape Signatures and Engineered Biosensors in Early Drug Discovery Process

Hartman, Izabela; Gillies, Alison R.; Arora, Sonia; Andaya, Christina; Royapet, Nitya; Welsh, William J.; Wood, David; Zauhar, Randy J.

doi:10.1007/s11095-009-9941-z

Cited by 23 publications

(17 citation statements)

References 35 publications

(59 reference statements)

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“…In previous work, we have demonstrated that these biosensors are capable of recognizing hormone like compounds for various human NHR targets, and can differentiate agonistic and antagonistic compounds (Skretas et al,2007). In several cases, drug‐like compounds initially identified by our bacterial sensors, including subtype‐selective agonists and antagonists, have been confirmed in subsequent human cell assays (Skretas et al,2007; Hartman et al,2009).…”

Section: Discussionmentioning

confidence: 65%

Bacterial biosensors for evaluating potential impacts of estrogenic endocrine disrupting compounds in multiple species

Gierach

Shapero

Eyster

et al. 2011

Environmental Toxicology

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To study the effects and possible mechanisms of suspected endocrine disrupting compounds (EDCs), a wide variety of assays have been developed. In this work, we generated engineered Escherichia coli biosensor strains that incorporate the ligand-binding domains (LBDs) of the β-subtype estrogen receptors (ERβ) from Solea solea (sole), and Sus scrofa (pig). These strains indicate the presence of ligands for these receptors by changes in growth phenotype, and can differentiate agonist from antagonist and give a rough indication of binding affinity via dose-response curves. The resulting strains were compared with our previously reported Homo sapiens ERβ biosensor strain. In initial tests, all three of the strains correctly identified estrogenic test compounds with a high degree of certainly (Z' typically greater than 0.5), including the weakly binding test compound bisphenol A (BPA) (Z' ≈ 0.1-0.3). The modular design of the sensing element in this strain allows quick development of new species-based biosensors by simple LBD swapping, suggesting its use in initial comparative analysis of EDC impacts across multiple species. Interestingly, the growth phenotypes of the biosensor strains indicate similar binding for highly estrogenic control compounds, but suggest differences in ligand binding for more weakly binding EDCs.

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Section: Discussionmentioning

confidence: 65%

Bacterial biosensors for evaluating potential impacts of estrogenic endocrine disrupting compounds in multiple species

Gierach

Shapero

Eyster

et al. 2011

Environmental Toxicology

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“…These signatures lend themselves to rapid comparison with each other for virtual screening of large chemical databases. Shape Signatures can be used by itself or in conjunction with currently available computational modeling approaches commonly employed in drug discovery and predictive toxicology, such as traditional virtual screening, descriptor-based (e.g., QSAR) models, ligand-receptor docking, and structure-based drug design [52, 64–67]. …”

Section: Modeling Frameworkmentioning

confidence: 99%

Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information

Sushko

Novotarskyi

Körner

et al. 2011

J Comput Aided Mol Des

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The Online Chemical Modeling Environment is a web-based platform that aims to automate and simplify the typical steps required for QSAR modeling. The platform consists of two major subsystems: the database of experimental measurements and the modeling framework. A user-contributed database contains a set of tools for easy input, search and modification of thousands of records. The OCHEM database is based on the wiki principle and focuses primarily on the quality and verifiability of the data. The database is tightly integrated with the modeling framework, which supports all the steps required to create a predictive model: data search, calculation and selection of a vast variety of molecular descriptors, application of machine learning methods, validation, analysis of the model and assessment of the applicability domain. As compared to other similar systems, OCHEM is not intended to re-implement the existing tools or models but rather to invite the original authors to contribute their results, make them publicly available, share them with other users and to become members of the growing research community. Our intention is to make OCHEM a widely used platform to perform the QSPR/QSAR studies online and share it with other users on the Web. The ultimate goal of OCHEM is collecting all possible chemoinformatics tools within one simple, reliable and user-friendly resource. The OCHEM is free for web users and it is available online at http://www.ochem.eu.

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“…In this work, we describe the fragment-based implementation of Shape Signatures, and demonstrate that it is a powerful tool for computer-aided drug design [8–12]. Essentially, we prove that the new methodology outperforms the older version by dramatically enhancing its selective power, while retaining all the advantages offered by the original implementation.…”

Section: Discussionmentioning

confidence: 99%

“…Since its introduction in 2003, the Shape Signatures method [8, 9] has proven a useful tool in a number of drug discovery projects [10–12] (including several proprietary investigations). The Shape Signatures technique uses a simple implementation of ray - tracing [13], a method borrowed from computer graphics imaging, to stochastically explore the volume enclosed by the solvent-accessible surface (SAS) of a ligand molecule, or the volume exterior to a protein receptor site.…”

Section: Introductionmentioning

confidence: 99%

Fragment-based Shape Signatures: a new tool for virtual screening and drug discovery

Zauhar

Gianti

Welsh³

2013

J Comput Aided Mol Des

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Since its introduction in 2003, the Shape Signatures method has been successfully applied in a number of drug design projects. Because it uses a ray-tracing approach to directly measure molecular shape and properties (as opposed to relying on chemical structure), it excels at scaffold hopping, and is extraordinarily easy to use. Despite its advantages, a significant drawback of the method has hampered its application to certain classes of problems; namely, when the chemical structures considered are large and contain heterogeneous ring-systems, the method produces descriptors that tend to merely measure the overall size of the molecule, and begin to lose selective power. To remedy this, the approach has been reformulated to automatically decompose compounds into fragments using ring systems as anchors, and to likewise partition the ray-trace in accordance with the fragment assignments. Subsequently, descriptors are generated that are fragment-based, and query and target molecules are compared by mapping query fragments onto target fragments in all ways consistent with the underlying chemical connectivity. This has proven to greatly extend the selective power of the method, while maintaining the ease of use and scaffold-hopping capabilities that characterized the original implementation. In this work, we provide a full conceptual description of the next generation Shape Signatures, and we underline the advantages of the method by discussing its practical applications to ligand-based virtual screening. The new approach can also be applied in receptor-based mode, where protein-binding sites (partitioned into subsites) can be matched against the new fragment-based Shape Signatures descriptors of library compounds.Electronic supplementary materialThe online version of this article (doi:10.1007/s10822-013-9698-7) contains supplementary material, which is available to authorized users.

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Application of Screening Methods, Shape Signatures and Engineered Biosensors in Early Drug Discovery Process

Abstract: This work demonstrates an effective combination of computational analysis and simple bacterial screens for rapid identification of potential hormone-like therapeutics.

Cited by 23 publications

References 35 publications

Bacterial biosensors for evaluating potential impacts of estrogenic endocrine disrupting compounds in multiple species

Bacterial biosensors for evaluating potential impacts of estrogenic endocrine disrupting compounds in multiple species

Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information

Fragment-based Shape Signatures: a new tool for virtual screening and drug discovery

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